The safety, energy density, output voltage, output current, and service lifetime of an electrical device such as a rechargeable electric storage battery or fuel cell may be improved by elimination of liquid electrolyte from the device. A liquid electrolyte may be toxic, flammable, or have a corrosive effect on other materials. Efforts have been made to remove liquid electrolyte from batteries and other devices by searching for materials which are solid state ionic conductors at room temperature. Materials with high conductivity at room temperature are preferred over materials with low conductivity. A solid state ionic conductor with high conductivity may be referred to as a superionic conductor material. Minimizing material cost is essential for some applications.
The properties of a solid state ionic conductor are influenced by the chemical formulation of the material, the crystalline structure of the material, temperature, and other factors. The number of candidate materials to be screened for use in a target battery, fuel cell, or sensor application may be so high as to make it impractical to synthesize and test more than a tiny fraction of the potential number of materials and crystalline structures. The complexity and time required for previously known numerical simulation strategies and laboratory analytical methods have limited evaluations of candidate materials to fewer than ten per year per researcher.
Computational methods based on molecular dynamics calculations have been used to predict candidate materials to be synthesized and tested for desirable material properties. However, previously known methods suffer from long computational execution times for screening each candidate material, leading to high costs for computer resources. For example, a previously known method for screening a candidate material performs multiple molecular dynamics calculations to calculate a set of diffusivity values “D” until the values of D converge with a preferred value of variance. Convergence may be achieved when a calculated value “2dDt” is greater than a preferred value, for example 60 angstroms, where “d” is the number of spatial dimensions, “t” represents a simulation time, that is, a duration of real-world time being simulated, and D may range in value from 10−12 cm2/s to 10−4 cm2/s. Furthermore, previously known methods have applied a normal distribution to the results of molecular dynamics calculations, possibly resulting in inaccurate values for D. Inaccuracies may become worse as simulation time “t” is reduced, for example when reducing a duration of real-world time being simulated to shorten an amount of execution time required to complete a simulation.
Execution times for computer programs using previously known methods for performing calculations to find a material with sufficiently high ionic conductivity for a selected application have been estimated to extend from about 3000 CPU-hours to about 3×1010 CPU-hours. Even at the lower end of the range of estimated computation execution times, previously known methods are too slow and too expensive in time, computer resources, and human resources to permit evaluation of many different material candidates within acceptable market windows for new consumer, commercial, or industrial products.